I was there, sitting in front of my media center, when I choose to take my laptop and do some research about women complexity. The first thing I did was to search on google to see how many time the topic have been used. The first link lead me to something a bit funny and a well designed animated gif.
After that I decided it would be best to analyze it my way… that means, with a lot of geekiness. Having got a course about Discrete Mathematics, where we talked about Algorithm Complexity, I though it would be cool to try to find an Big-O complexity for a women…. By the way, this post is only for fun and should not be use in reference for any thing that can be serious.
Let start:
I would like to quote a website I found, that explain in a very simple way what Algorithm Complexity mean
what does fast mean?
algorithms get slower the more items of data they deal with. that’s what we worry about when talking about algorithm speed.
a fast algorithm is one that can process a lot of data. we aren’t as concerned about which algorithm gets a certain job done first, but which would get that job done first if it involved a lot of data.
ok, so you might say an algorithm is fast if it can process a small amount of data very quickly. fine. but that’s not what i’m talking about here.
once again, we’re worried about what happens as the amount of data increases. a fast algorithm is less upset by a large amount of data.
http://www.acooke.org/andrew/complexity.html
This is a good start to understand algorithm complexity, but what the hell this have to do with women ? Well, I’m a man and I love a woman and I always want to see her happy and I’ve make it my goal. Unfortunately, sometimes it doesn’t work because it seems that I’m unable to understand her completely. So, to help myself I though it would be best to continue my research in finding a way to analyze the complexity of a women.
When I entered the words “big-o complexity women” in google, I got this …. It seems that for the women a Big-O complexity means something totally different… Well, entering “women” and “logic” inside google lead me to something a bit more interesting, I’m not sure if this Michael is totally right… but well he sure have a point when he say that a man must stay himself when dating a woman. There is another link that is fun to read.
Humm… we are still far from what I tried to do in this post… we still have to solve this “women=O( ? )”. The theory tell us that to analyze an algorithm we must observe how it behave with a lot of data. So, how could we found “?” in our equality using this statement ? Well lets search about how many data a women brain can compute. Doing some research lead me to this text where we can find that there is no significant difference between the brain of a man and the brain of a woman, so the problem is now more to find how the human brain compute the stuff. Wikipedia have a lot of information about the brain, in this entry it is said that a human brain contains 100 billions (100 000 000 000) neurons which are all linked to as many as 10 000 other neurons… That’s it ! Wikipedia gave me an answer when I was reading this section, according to Hans Moravec, the human brain “has a processing capacity of 100 trillion instructions per second (100 million MIPS).” Wow ! Thats a lot of processing power… well till the year 2030 then our personal computer may be faster…
Well, we have a number for the processing capacity, but we still doesn’t know how many information we receive in a second… So lets explore this a bit differently, we know that we have a lot of information for input but we don’t have a number… we simply know it’s an enormous amount of data. We will say it’s infinite, we learned in the link above that the brain have specific division to compute the information it receive and that each of them will divided the information into sub-division and so on. If we look at this we could think of an O(log n) complexity… but in my opinion it’s really not a good guess. A logarithmic complexity would mean that each division would use a constant (ex. always dividing by 2, like a dichotomic search) number of sub-division and it is unlikely to happen with a brain because the value change for all input. However, since the data size is infinite, we can say it would not have a too big impact so lets assume that O(log n) is a good clue. Now, when every sub-division are done with the data they send them back to be compute in group. Lost? Let me give you an example:
In a sunny sunday morning you are sitting near a river and a butterfly appear on rock infront of you. Your eyes will see the butterfly, they will send the information to the visual zone of the brain, exactly at the same moment that you ear will send the sound of the river to the auditory nerve, the freshness of the breeze will be send to your brain by your skin captor and smell of the spring will be send to your brain by your nose. The brain receive all of these informations in the same time, divided the job to every part involved then he have to mixed the result so he can analyze the new results. The butterfly may remind you of the hair clip of your girlfriend, but mixed with the sound of the river it’s now remembering you about your first encounter. Now the smell of the spring and the freshness of the breeze make you realized that you are in the middle of April, mixing all these informations together you remember that you first encounter your girlfriend the 15th of April beside a river… wait a minute your brain analyzed the information together again… man we are April 14th you gotta get a gift quick !
So you see, your brain constantly re-analyze all the informations when he got new one. So I think it would be more appropriate to think of an O(n log n) complexity for the brain. Wow, I did it, I have found a complexity for the brain. Well, it’s probably extremely inaccurate because I’m not a doctor and I don’t know it enough but well it was a lot of fun learning about all those links. Hope you enjoyed and maybe learn something.
For ending I’ll rely on xkcd.com to help me to explain my though… about love and women
PS: You may enjoy this text of philosophy its very interesting and totally different that everything I presented here.
LaMs
